Map-Matching Result Sharing Across Diverse Traffic Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems face challenges in efficiently sharing map-matching results between traffic ecosystem participants, leading to computational overhead and compatibility issues due to different map providers, which affects the accuracy and efficiency of location-based applications.
Innovation Solution
A system and method for sharing map-matching results among traffic participants, including vehicles and infrastructure, using a map-matching result sharing module that assembles and communicates messages containing map-matched location information, reducing the need for individual map-matching computations by participants and enabling harmonization of map data from different providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If each traffic participant performs individual map-matching computations using their own map data, then localization accuracy is improved, but computational burden and processing time increase significantly
Solution Approach 1:
The system performs map-matching computations in advance by a reference entity (server or lead vehicle) and stores the results. Other traffic participants can then directly utilize these pre-computed results without performing redundant calculations, significantly reducing their computational burden while maintaining localization accuracy.
Solution Approach 2:
Instead of each participant performing independent map-matching, the system creates and shares copies of map-matching results from a reference entity. Participants receive and use these copied results, eliminating the need for duplicate computational efforts while preserving the accuracy benefits of map-matching.
2Productivity
If map-matching results are shared among traffic participants, then computational burden is reduced, but compatibility issues arise due to different map providers
Solution Approach 1:
The system introduces a reference entity (server or lead vehicle) as an intermediary that standardizes map-matching results before sharing them with participants. This intermediary performs the map-matching using a reference map and transforms the results into a unified format, enabling participants with different map providers to compatibly share and use the standardized results.
Solution Approach 2:
The system transforms map-matching results into a standardized parameter format that is independent of the original map provider. By changing the representation parameters to a universal format, the system enables compatibility across different map data sources while preserving the essential location information.
3Loss of information
If map-matching results are shared with remote entities, then situational awareness is improved, but information accuracy may be compromised due to cross-entity map differences
Solution Approach 1:
The system transforms position information into map-matching results using a standardized reference map, changing the parameter representation to be independent of individual entity maps. This transformation ensures that shared information maintains accuracy and consistency across different entities while improving situational awareness.
Data Source
AI summary
A system for sharing a map-matching result is provided. The system comprises a map-matching module adapted for: receiving a digital map data from a map provider, receiving a location information, performing a map-matching on the received location information using the digital map data, and generating a map-matched location information. The system further comprises a map-matching result sharing module that is connected to the map-matching module. The map-matching result sharing module is adapted for receiving the map-matched location information from the map-matching module, and assembling a message including the map-matched location information as a map-matching result to be shared.